Cell characterisation

ABSTRACT

The present invention concerns the finding that non-coding RNA profiles can be exploited as a means of monitoring, assessing, comparing, establishing and/or determining certain cell characteristics and/or profiles. Accordingly, the invention provides the use of non-coding RNA molecules for characterising and/or profiling cells.

CROSS REFERENCE TO RELATED APPLICATIONS

This is a continuation of U.S. patent application Ser. No. 13/818,750,filed on Apr. 11, 2013, which is a national stage application ofInternational Patent Application No. PCT/GB2011/01241, filedinternationally on Aug. 19, 2011, which claims priority to UnitedKingdom Application GB1014049.9, filed on Aug. 23, 2010, all of whichare hereby incorporated by reference in their entireties.

FIELD OF THE INVENTION

The present invention provides uses of non-coding RNA in methods forcharacterising and/or profiling cells. In particular, the uses andmethods described herein may be exploited to assess the quality,identity, purity, potency and safety of cells and/or cell cultures.

BACKGROUND OF THE INVENTION

There has been rapid progress in biotechnology and medicine that has ledto the development of new treatments and medicinal products, among themproducts containing viable cells. These new cell-based products havegreat potential in the treatment of various diseases where there is anunmet medical need. The cell products are, in the case of stem cells,used directly for therapeutic purposes or are research tools to aid drugdiscovery by providing a homogenous source of stem cells, cellscommitted to differentiate to one or more lineages orterminally-differentiated cells of a particular lineage. Mammalian celllines used in research are vital tools for understanding basicbiological concepts while cells used in bioprocessing applications canyield macromolecules used for research purposes or clinicalapplications.

Current Characterisation and Safety Testing Methods.

There are a number of methods used to assess the quality, consistencyand potency of stem cells and cell cultures. For stem cells this isdefined as their self-renewal capacity and by the expression of specificmarkers. The identity of the desired cell population must be defined.Currently hESC lines are characterised using a set of standardisedmetrics: surface antigens, expression of particular enzymic activities(e.g. Alkaline phosphatase), gene expression, epigenetic markers,assessing genomic stability, cytology and morphology as well in vitro(embryonic body formation) and in vivo differentiation potential(formation of teratoma-like xenografts) and by the absence of measurablemicrobiological infections. However, the procedures used to assess thesestem cell characteristics require skilled staff, but have a relativelylow-information-content and are time-consuming and expensive. Inaddition they do not reveal crucial information on the safety profileand/or fitness-for-purpose of the resultant cells. There is a need forlow-skill, low-cost, information-rich QC assays and kits that inform onthe quality and consistency of the stem cell lines at derivation andunder continued passage in culture, including, for stem cells, expansionof cell populations under conditions supporting proliferation ofundifferentiated cells. These QC checks should also provide relevantbiological information on their likely suitability for purpose and, ifdeveloped for clinical use, their safety for deployment.

There is a requirement to continuously assess the inherent heterogeneityof human-based cell products in order to seek to minimise this variationduring the manufacturing of cell-based starting material.Correspondingly, there is a need for a relatively straightforward assaythat reports on both phenotypic drift of cells in culture and providesan assessment of the likelihood of their safety profile (e.g.tumourigenicity) if the cells are used as medicinal products.

MicroRNAs (miRNAs) are single-stranded RNA molecules having a length ofaround 18 to 25 nucleotides. miRNAs were first described by VictorAmbros in 1993 and since then over 2,000 papers on have been publishedon the subject of miRNAs. There are predicted to be about 1,000 miRNAsin humans, although some estimates place the figure at tens ofthousands. miRNA is not translated into protein but instead regulatesthe expression of one or more genes. Known biology currently shows thatmicroRNAs target particular individual messenger RNAs (mRNAs) or groupsof mRNAs, thereby preventing their translation or accelerating mRNAdegradation. The mature single stranded miRNA molecule complexes withthe RNA-Induced Silencing Complex (RISC) protein and binds to apartially complementary sequence within the 3′untranslated region(3′-UTR) of the protein coding mRNA from its target gene.

Further proteins are recruited to form a silencing complex and theexpression of the target gene product is repressed by a mechanism thatblocks the translation of the mRNA.

Although much remains to be discovered about the biology of miRNAs andthe composition and mechanism of action of the silencing complex it isapparent that miRNAs are involved in the regulation of many genes.MiRNAs are thought to regulate as many as 30% of all genes (Xie et al,2005) at the translational level. An miRNA can regulate multiple genesand each gene can be regulated by multiple miRNAs permitting complexinterrelationships between miRNA/mRNA networks within tissues and cells.

Tissue-specific expression of miRNAs is thought to guide commitment ofcells to differentiate and/or actively maintain cell or tissue identity.This wide-ranging influence and interplay between different miRNAssuggests that deregulated expression of a single miRNA or small sub-setof miRNAs may result in striking physiological or pathophysiologicalchanges and complex disease traits (Lim et al, 2005). More than 50% ofknown human miRNAs reside in genomic regions prone to alteration incancer cells (Calin et al, 2004). Not surprisingly, the expressionpattern of miRNAs change in cancer and other disease states. Thisinformation has begun to be used to classify and stage cancers, revealbiomarkers for prognosis and response and provide a critical determinantto guide therapeutic intervention.

An increasing body of evidence confirms that the expression levels ofindividual miRNAs vary significantly between cell types or within a celltype maintained under different physiological conditions and so can beused to define the cell type, the physiological status of the cell andmonitor response to environmental changes.

Embryonic and induced pluripotent stem cells are characterised by theirability to self-renew and differentiate into all cell types. Themolecular mechanisms behind this process are complex and rely on theinterplay between a network of transcription factors, epigeneticregulators, including miRNAs, and signalling pathways. MicroRNAs playessential roles in maintenance of pluripotency, proliferation anddifferentiation. Recent studies have begun to clarify the specific roleof miRNA in regulatory circuitries that control self-renewal andpluripotency of both embryonic stem cells and induced pluripotent stemcells. These advances point to a critical role for miRNAs in the processof reprogramming somatic cells to pluripotent cells.

We have used the ‘fingerprint’ patterns extracted from the informationcontent held within the miRNA expression profile of cells to monitor themaintenance of cell identity and functional capability. The miRNAprofile provides a unique insight into cell biology and can be reducedto practice through the development of kits to monitor pluripotency,cell-fate, cell-identity and phenotypic drift over multiple passagesusing a single development platform for microRNA screening.

The invention aims to provide alternative methods for monitoring thequality and suitability of cells for the purpose for which they weredeveloped.

SUMMARY OF THE INVENTION

The invention concerns methods employing non-coding RNA expressionassays as a means to characterise cells and/or to monitor the qualityand safety profile of in vitro cell culture systems.

Embodiments of the invention include, but are not limited to,determining the non-coding RNA/microRNA profile of cells and serialpassages of an in vitro cell culture system. The term “cell” should beunderstood to encompass any eukaryotic cell. For example a “cell” withinthe context of this invention may be a mammalian (adult, foetal orembryonic) cell including, for example a stem cell or iPS cell. In oneembodiment, a “cell system” according to this invention is (orcomprises): (i) pluripotent embryonic stem (ES) cells; (ii) inducedpluripotent stem cells (iPS) or ES or iPS cells and/or theirintermediate stages differentiating to one or more terminaldifferentiation states; (iii) adult stem cells (tissue-specificprogenitor cells or mesenchymal/stromal cells) or their intermediatesdifferentiating to one or more terminal differentiation states under theinfluence of external factors in the culture medium; mixtures of cellswith varying differentiation profiles; (iv) cell lines used in researchor engineered for bioprocessing e.g. for the production ofclinical-grade or research grade biological macromolecules. In oneembodiment, the “cells” may be fungal cells such as, for example, yeastcells. Cells and cell culture systems may be monitored under optimalgrowth conditions and/or under conditions where interventions, such asalterations to key element(s) of the growth maintenance regime of thecells is/are altered, so as to determine the affect on thenon-coding/microRNA profile of the cell.

The invention reveals sample clustering based on their microRNAexpression profile and identifies statistically valid, candidatenon-coding/microRNAs which are consistent and reliable markers ofundesirable or uncharacterised alterations in the cell system beingmonitored and therefore provide key decision-support tools on thecontinued usefulness of the cell system for their intended research,therapeutic or bioprocessing application.

The present invention concerns the finding that non-coding RNA profilescan be exploited as a means of monitoring, assessing, comparing,establishing and/or determining certain cell characteristics and/orprofiles. In one embodiment, the various uses and/or methods describedherein may be exploited to determine, monitor, establish, compare and/orassess cell characteristics which are also markers of cell qualityand/or safety.

Accordingly, and in a first aspect, the present invention provides theuse of non-coding RNA molecules for characterising and/or profilingcells.

The inventors have determined that profiles of non-coding RNA moleculeexpression (referred to hereinafter as non-coding RNA expressionprofiles) provide a “fingerprint” which can be correlated to, linked ormatched with, the presence of particular cell characteristics and/orcertain cell profiles. By establishing a non-coding RNA expressionprofile indicative of one or more cell characteristic(s) or a particularcell profile, it is possible to assess other cells for correspondingcharacteristics and/or profiles by simple comparison of the non-codingRNA expression profiles. Additionally, the inventors have surprisinglydiscovered that cells which are shown to be phenotypically identical bystandard analytical techniques (such as, for example by flow cytometryand/or cell surface/cytoplasmic/nuclear marker analysis and the like)can be shown by the micro-RNA profiling techniques described herein, tobe genotypically (and thus most likely phenotypically)distinct/different. Where cell safety and quality are concerned, thephenotypic differences between an un-safe (for example tumorogenic) cellor cells and/or a cell of poor quality (perhaps lacking expression ofspecific markers), may be undetectable by standard techniques.

The instant invention provides a highly sensitive an accurate means ofestablishing whether or not a cell or cell system (for example thepopulation of cells within a cell culture) conforms to a set ofpredetermined standards. One of skill will appreciate that provided oneestablishes a micro-RNA profile of a cell which is known to conform to aset of predetermined safety and/or quality standards, other cells of thesame type can be assessed for conformity with the predetermined safetyand/or quality standards by comparison of micro-RNA.

In view of the above, one embodiment of this invention, provides the useof non-coding RNA molecules for characterising and/or profiling cells,wherein the cells are shown to be phenotypically identical to areference cell by methods other than micro-RNA profiling. In oneembodiment, the method by which the cell and a reference cell are shownto be identical may be flow cytometry. In this context, a reference cellmay be a cell conforming to a predetermined set of safety and/or qualitystandards.

In one embodiment, the methods provided by this invention may excludemethods which exploit micro-RNA profiling to distinguish onedifferentiative cell state from another. For example, in someembodiments, the invention may not embrace the use of micro-RNAprofiling to assess the differentiation of stem cells to other celltypes.

A second aspect of this invention provides a method of characterisingand/or profiling a cell, said method comprising the steps of comparingthe non-coding RNA profile of said cell with a reference non-coding RNAexpression profile. In one embodiment, the reference non-coding RNAexpression profile may be derived from a cell possessing characteristicsand/or a profile which should be present and/or exhibited by the cellbeing characterised/profiled.

It should be understood that a cell “characteristic” or “profile” mayrelate to cell features such as identity (type), morphology, genotype,phenotype, viability, potency (for example degree of pluripotency),contaminant levels, safety (for example tumourigenicity) and/or quality.In certain embodiments, a cell “profile” may be determined byestablishing aspects of one or more of a cell's morphology, genotype,phenotype, viability, potency (pluripotency), contaminant levels, safety(tumourigencity) and/or quality. One of skill will appreciate that theterms cell “characteristic” and/or “profile” may relate to thebiological activity and/or compound secretion/production profile. By wayof example, a cell characteristic and/or profile may relate to theability of a cell to express, produce and/or secrete a natural ofheterologous compound or compounds such as, for example, a protein,peptide, amino acid, nucleic acid, carbohydrate and/or other smallorganic compound.

The term “non-coding RNA” may include microRNA (miRNA) molecules andeither or both miRNA precursors and mature miRNAs. The term may furtherinclude small interfering RNAs (siRNA), piwi-interacting RNAs (pi RNA),small nuclear RNA (snRNA) and short hairpin RNA (shRNA). “Non-codingRNA” according to this invention may further comprise transgenicnon-coding RNAs which may function as reporters of non-coding RNAexpression. The non-coding RNAs may be episomal and the methods and/oruses described herein may require initial steps in which episomal DNA isintroduced into the cells described herein whereupon the episomal DNAcan be transcribed to produce non-coding RNA which constitutes all orpart of the profiled non-coding RNA. In one embodiment, the term“non-coding RNA” does not include non-coding RNAs known as “teloRNA” or“teloRNA mark”.

A non-coding RNA expression profile may relate to the expression and/oridentity of at least one non-coding RNA. In one embodiment, thenon-coding RNA expression profile relates to the expression of aplurality of non-coding RNAs. Accordingly, a non-coding RNA expressionprofile may comprise some indication of the identity of one or morenon-coding RNAs expressed by a cell optionally together withquantitative and/or qualitative measurements of the level of expressionof one or more non-coding RNAs within a cell.

In certain embodiments, the methods and uses described herein mayrequire the use of a non-coding RNA expression profile database. Such adatabase may be referred to as a non-coding RNA reference library.Non-coding RNA databases described herein may comprise one or morereference non-coding RNA profiles each being derived from a cell havingknown characteristics/profiles and/or cells which have been culturedaccording to a particular protocol and/or subjected to known or definedinterventions.

In one embodiment, the reference non-coding RNA profiles may be derivedfrom an isolated cell, cells derived from a cell culture, cell lineand/or stored cell preparation. Additionally or alternatively, thereference non-coding RNA profiles may be obtained from cells subjectedto one or more defined or predetermined interventions and/or cellssubjected to a particular culture protocol, altered culture conditionsand/or one or more interventions. The reference non-coding RNA profilesdescribed herein, may comprise non-coding RNA profiles derived fromsingle cell types and/or a plurality of different cell types. In otherembodiments, the reference non-coding RNA profile may be derived fromprimary cell cultures and/or immortalised cells. Advantageously, thereference non-coding RNA profile is obtained from a cell or cellexhibiting known and/or desired characteristic(s), a desired and/orcorrect profile and/or an a cell or cells which meet a certainpredetermined quality and/or standard.

Since the reference non-coding RNA expression profiles are derived fromcells exhibiting known (desirable) characteristics and/or profiles, oneof skill will appreciate that any cell which exhibits a comparablenon-coding RNA profile, must possess similar characteristic(s) or asimilar profile.

The reference non-coding RNA expression profiles may be compiled usingmultiple sets of data obtained from repeat non-coding RNA expressionanalysis of cells having known characteristics and/or known profilesand/or from non-coding RNA expression analysis of cells conforming toknown or approved standards.

For convenience, the reference micro-RNA profiles described herein maybe referred to as “comparative micro-RNA profiles”.

The process of comparing non-coding RNA expression profiles obtainedfrom cells to be characterised, profiled and/or quality assessed, withreference non-coding RNA profiles (optionally contained within adatabase) as described herein, may involve identifying correlationsbetween non-coding RNA profiles. Correlations between non-coding RNAprofiles of cells being characterised, profiled and/or quality assessedare typically correlations, positive or negative, between changes in theexpression of one or more non-coding RNAs. For example, a positivecorrelation may comprise the identification of a particular non-codingRNA profile in a cell being characterised, profiled or qualitycontrolled and the same non-coding RNA profile in reference non-codingRNA profile (or database). A negative correlation may comprise theidentification of a particular non-coding RNA profile in a cell beingcharacterised, profiled or quality controlled and a reference non-codingRNA profile which, while exhibiting expression of correspondingnon-coding RNAs—exhibits variable or differential expression levels(i.e. the expression of a particular non-coding RNA in a referenceprofile may be less than when compared to the expression of the samenon-coding RNA identified in a cell being characterised, profiled and/orquality controlled).

The reference non-coding profiles and/or databases described herein maycomprise non-coding RNA expression profiles which have been categorised(clustered or grouped) on the basis of similarities present in thereference non-coding RNA profiles. For example, data relating toparticular cell types and/or to cells cultured in a particular way, maybe grouped together so as to facilitate probing a database forcorrelations with non-coding RNA profiles of cells being characterised,profiled and/or quality controlled.

In view of the above, the non-coding RNA profiles contained within thereference non-coding profiles provided by this invention may representthe profiles of one or more types of cell, cells at various stages ofculture, cells cultured according to particular protocols and/or cellssubject to one or more interventions—perhaps an intervention occurringduring culture.

The term “intervention” may be taken to include the act of administeringa compound or compounds to a cell. In other embodiments, an interventionmay include the change of culture media, the addition of one or moremedia supplements as well as alterations in culture conditions such as,for example, time, temperature, pH and/or osmolality. An interventionmay also include the transfer of cells from one culture vessel toanother—perhaps as a result of cell sub-culturing procedures.

The present invention finds particular application in the field of cellculture where it may be necessary to ensure that one or more cellinterventions or protocols has not had a deleterious effect on the cellsof the cell culture. For example, by compiling a reference non-codingprofile of cells which exhibit favourable or desired characteristicsbefore during and/or after successful culture according to one or moreprotocols, it may be possible to establish whether other cells culturedaccording to the same protocols exhibit the same characteristics before,during and/or after culture, by simple comparison of non-coding RNAprofiles.

Where the reference non-coding RNA profiles are intended to representthe characteristics and/or features of cells being cultured, non-codingRNA profiles may be obtained from serially passaged (split and/orsubcultured) cultures of cells either at or during each passage and/orat various other points during culture. Additionally, or alternatively,when culture conditions are altered or the cells of the culture aresubject to an intervention (perhaps the addition of a supplement(antibiotic, nutrient or the like), a reference non-coding RNAexpression profile may be obtained.

In this way, it is possible to construct a database comprising one ormore reference non-coding RNA profiles which reflect the non-coding RNAprofiles of cells in culture. One of skill will appreciate that such adatabase may be used to monitor and/or assess cell cultures bycomparison of the non-coding RNA profiles of cells from the cell culturewith the reference non-coding RNA profiles of the database.

In one embodiment, the methods provided by this invention may be used toassess the effect of specific culture substrates (or components thereof)on cells and cell cultures. For example, the methods of this inventionmay be exploited as a means of assessing or monitoring the performanceof nanofibres/nanoscale growth surfaces which can be used to maintainthe pluripotency or a specific differentiative state of stem cells. Insuch cases, a micro-RNA profile indicative of a pluripotent cell orcorrectly differentiated cell would be obtained and compared to themicro-RNA profile of cell cultured on a nanofibres/nanoscale growthsurface in order to determine whether or not the cells remainpluripotent or correctly differentiated.

In other embodiment, the micro-RNA profiling methods provided by thisinvention may be exploited to assess the effectiveness of alyophilisation technique or the viability of cells subjected to such aprocess. Again, comparative micro-RNA profiles would be obtained fromcells before and after a lyophilisation process and/or cells whichremain viable after lyophilisation. Such techniques could be applied toerythrocyte lyophilisation protocols.

In yet further embodiments, the micro-RNA profiling provided by thisinvention may be used to assess the effectiveness of protocols whichforce the differentiation of one cell type from another. Such protocolsmay include those which cause differentiation without a pluripotentintermediate. By way of example, the micro-RNA profiling methods of thisinvention may be used to assess the success of a fibroblast/erythrocytedifferentiation protocol, a comparative micro-RNA profile being obtainedfrom a correctly differentiated erythrocyte cell.

Non-coding RNA expression profiles may be measured or determined foreach non-coding RNA within a particular group or subset of non-codingRNAs. Additionally, or alternatively, non-coding RNA expression profilesmay comprise the identification of an individual non-coding RNA andmeasuring and/or determining the expression thereof.

The level of expression may be determined indirectly via measurements ofthe amount or level of activation of a reporter construct, for example atransgenic reporter construct incorporated into the genome of a cell.

The methods and uses of this invention may find particular applicationin cell quality control and/or safety analysis procedures. One of skillin this field will appreciate that commercial production, sale anddistribution of cells—particularly cells derived from stored cell lines,is subject to stringent quality and safety control, primarily to ensurethat stored cells and/or cells distributed to customers, meet certainpredetermined standards. For example it may be necessary to ensure thatcells cultured from stored cell lines are as described (both in terms ofidentity and morphology), are viable and exhibit certain characteristics(features and/or traits).

Current cell quality control processes or procedures, may involve aseries of complex, time consuming and costly tests—each of which isdesigned to confirm that a cell meets a pre-determined standard. Suchtests may be performed prior to shipping a cell line to a customer butalso at regular intervals during storage or culture. By way of example,cell quality control procedures may comprise tests designed to assesscell identity/morphology, cell phenotype, cell genotype, levels of cellcontamination, degree of pluripotency, cell viability and/or cellsafety. Such tests may involve the use of DNA profiling techniques,immunohistochemistry, alkaline phosphatase staining, flow cytometry,gene expression analysis (perhaps using expression arrays and the like),blood group typing, karyology, microorganism screening (using PCR andimmunological based techniques), teratoma and embryoid body formation(particularly relevant where the pluripotency of a stem cell is beingtested) and simple live/dead (trypan blue) stains to determineviability.

By establishing a reference or comparative non-coding RNA profileindicative of a certain cell “standard” or “quality standard”, it ispossible to quality control cells by comparison of non-coding RNAprofiles. By way of example, the non-coding RNA profile of a cellcultured from a stored cell line may be compared with the non-coding RNAprofile (i.e. a reference non-coding RNA profile) of the same type ofcell which is known to meet one or more predetermined standards. If thenon-coding RNA profile of the cell being cultured is comparable to, ormatches with, the (reference) non-coding RNA profile derived from a cellknown to meet one or more pre-determined standards, one may concludethat the cultured cell meets the same standards.

It should be understood that the term “standard” or “quality standard”may relate to defined criteria or features which any given cell mustexhibit prior to being used (in anyway whatsoever), sold or distributed.Such standards may be set by regulatory bodies but may also relate tolocally determined cell features and/or characteristics which rendercells suitable for particular uses—for example uses in assays and thelike.

In view of the above, the present invention provides use of non-codingRNA profiles in cell quality control.

In a further embodiment, the invention provides a method of qualitycontrolling cells, comprising the steps of comparing the non coding RNAprofile of cells to be quality controlled, with a reference non-codingRNA profile. In one embodiment, the reference non-coding RNA profilesmay be derived from a cell or cells known to meet a certain qualitystandard. Since the reference non-coding RNA profiles are derived from acell meeting one or more predetermined standard(s), any cell whichexhibits a non-coding RNA profile corresponding to a referencenon-coding RNA profile, must be of a similar quality standard. In oneembodiment, the non-RNA profile of the cell to be quality controlled maybe compared with a database comprising one or more reference non-codingRNA profiles.

In one embodiment, the quality control procedures comprise establishingthe identity, phenotype, genotype, levels of contamination, viabilityand/or pluripotency in stored and/or cultured cells.

Advantageously, the reference non-coding RNA profiles described hereinmay be derived from cells of known identify and having definedphenotypes and/or genotypes, known levels of contamination (low/nocontamination, moderate or high levels of contamination), definedpluripotency (for example complete, partial or no pluripotency), anddefined levels of viability.

For example, methods for assessing the pluripotency of a cell maycomprise the step of comparing the non-coding RNA profile of a cell withunknown pluripotency with the non-coding RNA profile of the same type ofcell having a known level of pluripotency.

Similarly, cell identity may be confirmed by comparing the non-codingRNA profile of a cell (perhaps a cell of unknown identity) with thenon-coding RNA profiles of a cell of known identity. If the non-codingRNA profile of the unknown cell corresponds to, or matches with, thenon-coding RNA profile of any of the known cells, then it may beconcluded that the unknown cell is the same as the cell from which thecorresponding or matching non-coding RNA profile was derived.

In one embodiment, the methods described herein may be exploited toestablish a level of Mycoplasma contamination in a cell or cells. One ofskill will appreciate that a comparative or reference micro-RNA profilemay be obtained from a corresponding cell type or cell population knownto be free from Mycoplasma contamination.

One of skill will appreciate that the present invention, and inparticular those embodiments relating to cell quality control, findsparticular application in the field of cell culture, particularlycommercial cell culture where large numbers of cells are stored andcultured.

When culturing cells, it is often important to make regular checks toensure that the cultures comprise cells which meet certain predeterminedstandards. For example, beyond establishing that the cultured cells areof the correct cell type, it may be necessary to ensure that the cellexpresses certain markers or that the cell expresses a particularcompound or compounds or that interventions which occur during cellculture do not have a deleterious effect upon the cells. Where the cellculture comprises stem cells, it may be necessary to ensure that thecells of the culture comprises cells which remain pluripotent throughoutpassage and/or that the cell follows a particular differentiation path.By comparing the non-coding RNA profiles of cultured cells with thenon-coding RNA profiles of cultured cells conforming to known orpredetermined culture standards, it is possible to ensure that the cellsbeing cultured meet those same standards.

In one embodiment, a database comprising one or more referencenon-coding RNA profiles may comprise non-coding RNA profiles obtainedfrom cells being serially passaged and at various stages of culture. Forexample, the database may comprise the non-coding RNA profiles of one ormore different types of cells during early-, mid- and/or late-phasepassage or culture or at any other time point there between.Additionally or alternatively, the database may contain the non-codingRNA profiles of cells which have been subjected to some form of alteredculture condition (for example altered time, temperature, pH, nutrientand/or metabolite availability). In other embodiment, the database maycontain non-coding RNA profiles obtained from one or more cells whichhave been contacted with various agents such as, for example, growthmedia supplements including, vitamins, nutrients, nucleic acids,antibiotics, candidate drug compounds, test agents, antibodies,carbohydrates, proteins, peptides and/or amino acids. It should beunderstood that the database may contain many such non-coding profilesobtained from a variety of different cell types.

One of skill will appreciate that the data comprising the referencenon-coding RNA profiles may be compared with data from cells beingtested, with the aid of data processing/analysis techniques such as, forexample statistical mathematical methods. For example, techniques suchas principle component analysis or pattern recognition algorithms may beused to identify correlations between data contained within the databaseand non-coding RNA expression profiles obtained from cells being tested.

In other aspects, the invention may provide a kit for characterising,profiling and/or quality controlling cells, said kit comprising adatabase of one or more reference non-coding RNA profiles and assaysystems, apparatus and/or reagents necessary to obtain non-coding RNAprofiles from cells to be characterised, profiled and/or qualitycontrolled. The user may simply obtain the non-coding RNA profile of acell to be characterised, profiled and/or quality controlled and simplycompare the non-coding RNA profile with the non-coding RNA profile(s) ofthe database.

In a further aspect, the present invention may relate to a cellcharacterisation, profiling and/or quality control service whereby aservice provider receives cells from third parties to be characterised,profiled and/or quality controlled. The service provider may have one ormore non-coding RNA databases of the type described herein and which canbe used to compare the non-coding RNA profiles of the cells provided bythe third parties. Once the non-coding RNA profiles of the cellsprovided by the third parties have been compared with the non-coding RNAprofiles of database, the third party may then be provide with a reportdetailing information relating to the characteristics, profile and/orquality of the cells.

Such a service may be particularly useful to third parties involved incell storage and/or culture. The service may be of particular use tothose who are required to make regular checks of cells in storage orculture to determine cell identity/type, cell phentotype/genotype,viability, pluripotency, levels of contamination and the like.Furthermore, the services described herein may be used to ensure thatcells subjected to particular interventions or culture protocols possessthe required characteristics before, during and after execution of theprotocol and/or intervention.

The third party may further provide information relating to the cultureprotocols used to culture the cells and/or information relating tocertain features, traits and/or characteristics the cells to becharacterised, profiled and/or quality controlled, should have.

DETAILED DESCRIPTION

The present invention will now be described in detail with reference tothe following figures which show:

FIG. 1 is a flow diagram of a method according to the invention;

FIGS. 2A-2E are graphs showing decreased expression of hsa-miRNA-210 andincreased expression of hsa-miR-1274a and hsa-miR-302c* with extend invitro passage of hESCs with both microarray and QPCR data panels; FIG.2A shows a Principal Components Analysis revealing separation of samplesbased on cell passage number in human embroyonic stem cell line RCM1;FIG. 2B shows an expression profile analysis of micro RNA microarrayexpression data (normalised signal intensities from the array) forhsa-miR-210 and three other microRNA which do not significantly changeexpression between passages; and FIGS. 2C-2E show confirmation of keymicroRNA expression differences by qRT-PCR data;

FIGS. 3A-3E show phenotypic ‘drift’ of human cancer-derived cell lines(HeLa and MCF-7) with extended passaging in vitro; FIG. 3A is a graphshowing alterations in microRNA profiles in a serially passaged human,tumour-derived cell lines (HeLa and MCF-7); principal componentsanalysis of microRNA datasets reveals separation of samples based oncell passage number in MCF-7 cells; FIG. 3B is a table showing twentymiRNAs altered during serial passage of MCF-7 cells in culture. Alltwenty miRNAs show significant decreases in gene expression over theseven passages monitored. The changes are shown as relative changes(fold changes) in comparison to the earliest passage (P3) cells. FIG. 3Cshows a profile analysis of the twenty miRNAs of FIG. 3B; FIG. 3D showstwenty miRNAs altered during serial passage of HeLa cells in culture.All twenty miRNAs show significant alterations in miRNA expression overthe seven passages monitored. The changes are shown as relative changes(fold changes) in comparison to the earliest passage (P3) cells. FIG. 3Eshows a profile analysis of the twenty miRNAs of FIG. 3D;

FIG. 4A shows Flow Cytometry results for 2 hESC populations that aremaintained under identical culture conditions for extended passages;

FIG. 4B shows principal component analysis (PCA) of miRNA profile of theMid- and High-passage hESC populations;

FIG. 4C shows a volcano plot representing the differential expression ofmicroRNA between mid-passage (P51) and high-passage (P103) cells. The 5differentially-expressed miRNAs with a fold-change difference of 2 ormore are circled in red;

FIG. 4D shows the identification of 5 microRNAs (circled red in FIG. 4C)which demonstrate a greater than 2-fold differential expression betweenP51 and P103 hESC cultures; and

FIGS. 5A and 5B are graphs showing clustering of different sample groupsbased on differences in miRNA expression profiles. A. FIG. 5A shows aprincipal component analysis (PCA) where the arrows denote thetrajectories of differentiation; B. FIG. 5B show sample relationshipsusing hierarchical clustering and a heatmap.

EXAMPLE 1

In an example application of the invention, a database of miRNAexpression data sets (being an example of an expression data set derivedfrom a measured non-coding RNA expression profile) are prepared. Withreference to FIG. 1, suitable human embryonic stem cells are cultured byknown methods over an extended period of time and sampled at 3 pointsafter their derivation i.e. at passages 38, 51 and 103. A miRNAexpression profile is then measured using a sample of the cells at eachpassage to determine the expression level of each of a number of miRNAsin the treated cells.

Two alternative methods for measuring the miRNA expression profiles,microarray analysis and qualitative real-time PCR analysis, are set outbelow.

(1) miRNA Microarray and Data Analysis

Total RNA from reference cells (n=3) is isolated using a column-basedkit from Exiqon A/S of Vedbaek, Denmark. Two μg of total RNA from eachsample is analysed by miRNA microarray. miRNA microarray analysisincluding labelling, hybridization, scanning, normalization and dataanalysis is commercially available from a number of sources, forexample, from Exiqon A/S. Briefly, RNA Quality Control is performedusing Bioanalyser 2100 microfluidics platform (Bioanalyser is a trademark of Agilent Technologies). Samples are labelled using the CompleteLabelling Hyb Kit from Agilent, following the provided instructions.

(2) Quantitative Real-Time PCR

As with option (1) above, all cellular RNA is extracted using acolumn-based kit from Exiqon and following the manufacturer'sinstructions. Quantification of miRNAs by TaqMan Real-Time PCR iscarried out as described by the manufacturer (Applied Biosystems ofFoster City, Calif., USA). (TaqMan is a trade mark of Roche MolecularSystems, Inc.). Briefly, 10 ng of RNA is used as a template for reversetranscription (RT) using the TaqMan MicroRNA Reverse Transcription Kitand miRNA-specific stem-loop primers (Applied Biosystems). An aliquot(1.5 μl) of the RT product is introduced into 20 μl PCR reactions whichare incubated in 96-well plates on the ABI 7900HT thermocycler (AppliedBiosystems) at 95° C. for 10 min, followed by 40 cycles of 95° C. for 15s and 60° C. for 1 min. Target gene expression is normalized betweendifferent samples based on the values of U48 RNA (a small, non-codingRNA) expression (or U6 RNA, if U48 is found to vary between samples).

Experimental Findings and their Implications.

Using the methods described we have established that it is possible todetermine a novel way to monitor the identify the phenotypic drift ofcells based on the grouping of miRNA expression data. Furthermore, themethod can be employed to identify certain miRNAs, having expressionlevels which are indicative of potential alterations in cellularfunctions including pluripotentcy and tumourigenicity. These miRNAs willenable future intervention screening to analyse a relatively small groupof miRNA expression levels changes to identify key alterations in cellphysiology/pathophysiology with specific subsets, and not the entiremiRNA repertoire, being used depending on the particular endpoint beinginvestigated.

An example of using a select small group of miRNAs to determinepotential Safety of a human embryonic stem cell population is givenbelow.

Materials and Methods

RCM1 Cell Culture.

Derivation

The cell line RCM-1 was derived from a freshly received Day 6Blastocyst. It was manually hatched using a Swemed Stem Cell cuttingtool (Vitrolife AB, Cat No: 14601) and the inner cell mass isolated andplated onto human fibroblasts (Cascade Biologies). The fibroblasts hadbeen pre-plated onto tissue culture wells which in turn had beenpre-coated with a layer of human Laminin (Sigma, Cat No: L4544). Thecells were cultured in conditioned medium containing 24 ng/ml humanbasic fibroblast growth factor (hbFGF) (Invitrogen, Cat No: PHG0261).The resultant outgrowth was manually passaged using a Swemed Stem Cellcutting tool and through early expansion continued to display a typicalundifferentiated morphology while on the laminin/feeders plus hbFGFculture system.

The characteristics of the cell line represented in the summary documentavailable online athttp://www.roslincells.com/sitepix/downloads/RCM-1.pdf

Expansion

RCM-1 was then adapted to a feeder-free culture system of CellSTARTmatrix (CS) (Invitrogen, Cat No: A10142-01) with StemPRO (SP)(Invitrogen, Cat No: A1000701) medium containing 8 ng/ml hbFGF and underthese conditions has maintained an undifferentiated morphology. The cellline was expanded through a number of passages using mechanical/manualmethods in preference to enzymatic methods. At various passage stages,during the expansion of the cell line, cells were cryopreserved, asdescribed and following manufactures instructions, using CryoStor CS10(Stemcell Technologies, Cat No: 07930). Recovery from Cryopreservation

Three passage time-points, early, mid and late were thawed for thestudy, namely passages P38, P51 and PI 03.

Vials, in triplicate, were removed from −150° C. freezer and quicklythawed at 37° C. The thawed cells were them washed twice in pre-warmedmedium before being resuspended in fresh pre-warmed medium and platedinto wells in a culture system of CellSTART matrix (CS) (Invitrogen)with StemPRO (SP) media containing 8 ng/ml hbFGF.

Cells were cultured for 7 days (FIG. 1), with repeated medium changes,before harvesting for RNA extraction (see below).

Flow Cytometry Analysis

The cells which were harvested for RNA extraction were also sampled todetermine the expression of the multiple markers of pluripotency anddifferentiation.

A single cell suspension was made from the remaining cells in cultureand stained for the various markers associated with either adifferentiated or undifferentiated state. The markers stained for were:stage-specific embryonic antigen 1 (SSEA-1) where an up regulation isindicative of a differentiated state, stage-specific embryonic antigen 4(SSEA-4) where an up regulation is indicative of an undifferentiatedstate and Oct3/4, a 34 kDa POU transcription factor that is expressed inembryonic stem (ES) cells and germ cells, and its expression is requiredto sustain cell self-renewal and pluripotency, using a Human and MousePluripotent Stem Cell Analysis Kit (BD, Cat No: 560477).

The stained cells are analysed using Flow Cytometry and the resultsproduced give the status of the cell line both numerically andgraphically for the markers analysedas shown in FIG. 4A.

Tumour-Derived Cell Lines

HeLa and MCF-7 cells were cultured and passaged (sub-cultured) usingstandard methods.

RNA Extraction

Prior to miRNA profiling analysis, total RNA must be isolated from thecells, and analysed for quality. Total RNA from stem cells, at differentpassage numbers, is isolated using the miRCURY RNA isolation kit,obtainable from Exiqon (Denmark). Following the manufacturer'sinstructions, the cells are lysed in the tissue culture dish using aspecific lysis buffer, and transferred to a column where the RNA iswashed then eluted. RNA quantity and quality is checked using theNanodrop ND-1000 spectrophotometer (Thermo Fisher of Waltham, Mass.,USA) and the Bioanalyser 2100 microfluids-based platform (AgilentTechnologies of Santa Clara, Calif., USA).

Micro RNA expression profiles for stem cell samples of different passagenumbers can be determined by isolating total RNA from these samples andanalysing them by two methods; (1) miRNA microarray and:

(2) Quantitative Real-Time PCR (QPCR).

Microarrays are used to achieve a complete miRNA profile of a sample, bycollecting data on the expression levels of human 851 miRNAssimultaneously. QPCR is used to interrogate an individual miRNA ofinterest in a number of samples so differences in expression levels canbe determined.

(1) miRNA Microarray and Data Analysis

Total RNA that has been checked for quality and has been diluted to anappropriate concentration is used as the starting material for miRNAprofiling on the Agilent microarray platform. 100 ng of total RNA fromeach sample is processed through the microarray protocol, in which themicroRNAs are labelled, hybridised to an array and scanned using theAgilent Microarray Scanner. Samples are labelled with Cy3 dye using theAgilent ‘miRNA Complete Labeling and Hyb kit’ and hybridised overnighton an Agilent miRNA array, 8 of which are found on each glass slide. Onan array, each miRNA is represented 16 times, by at least 2 differentprobes. In addition, spike-in controls are used to evaluate thelabelling and hybridisation efficiency of the reactions. Scanned imagesof the arrays constitute the input for the Agilent Feature Extractionsoftware, which analyses each spot on the image, assigning it to aspecific miRNA and calculating a value for the emitted fluorescentsignal. The output from this processing is a series of QC reports, whichevaluate the quality of the array processing, and text files, whichcontain the raw microarray data. These text files form the basis of thestatistical analysis which is used to identify changes in miRNAexpression between different samples. For best experimental design,biological replicates (n=3) are processed on different slides to ensurereproducibility. Microarray data is interpreted by statistical analysisprograms such as GeneSpring (Agilent Technologies) and/or Omics Explorer(Qlucore of Lund, Sweden), and by Sistemic's in-house statisticalmethods (see below).

RNA Extraction

RNA was isolated and purified from these cells using a column-based kitfrom Exiqon the following procedure. The medium the cells were grown onwas aspirated and the cell monolayer was washed with an appropriateamount of PBS. The PBS was further aspirated. 350 μL, of the lysissolution was added directly to a culture plate. The cells were lysed bygently tapping the culture dish and swirling buffer around the platesurface for five minutes. The lysate was then transferred to amicro-centrifuge tube. 200 of 95-100% ethanol was added to the lysateand mixed by vortexing for 10 seconds. A column was assembled using oneof the tubes provided 1 in the kit. 600 μL of the lysate/ethanol wasapplied onto the column and centrifuged for 1 minute at 14,000×g. Theflow-through was discarded and the spin column was reassembled with itscollection tube. 400 μL of the supplied wash solution was applied to thecolumn and centrifuged for 1 minute at 14,000×g. The flow-through wasdiscarded and the spin column was reassembled with its collection tube.The column was washed twice more by adding another 400 μL of washsolution and centrifuging for 1 minute at 14,000×g. The flow-through wasdiscarded and the spin column was reassembled with its collection tube.The column was spun for two minutes at 14,000×g to thoroughly dry theresin and the collection tube was discarded. The column was assembledinto a 1.7 mL elution tube provided with kit. 50 μL of elution bufferwas added to the column and centrifuged for two minutes at 200×gfollowed by one minute at 14,000×g. The resulting purified RNA samplecould be stored at −20° C. for a few days. For long 22 term storage ofsamples were stored at −70° C.

(1) miRNA Microarray and Data Analysis

Labelling

Purified RNA samples were labelled using a labelling kit from Agilent.The total RNA sample was diluted to 50 ng/μL in 1×TE pH 7.5. 2μï. of thediluted total RNA was added to a 1.5 mL micro-centrifuge tube and put onice. Immediately prior to use, 0.4 μL 10×calf intestinal phosphatasebuffer, 1.1 μL nuclease free water and 0.5 μL calf intestinalphosphatase were gently mixed to prepare a calf intestinal alkalinephosphatase master mix. 2 μL of the calf intestinal alkaline phosphatasemaster mix was added to each sample tube for a total reaction volume 4μL, and was gently mixed by pipetting. The reaction volume was incubatedat 37° C. in a circulating water bath for 30 minutes. 2.8 μL of 100%DMSO was added to each sample. Samples were incubated at 100° C. in acirculating water bath for 5-10 minutes and then immediately transferredto an ice bath.

10×T4 RNA ligase buffer was warmed to 37° C. and spun until allprecipitate had dissolved. Immediately prior to use, 1 μL of 10×T4 RNAligase buffer, 3 cyanine3-pCp and 0.5 μL T4 RNA ligase were gently mixedto make a ligation master mix and put on ice. 4.5 μL of the ligationmaster mix was added to each sample tube for a total reaction volume of11.3 μL. Samples were gently mixed by pipetting and spun down. Thesamples were then incubated at 16° C. in a circulating waterbath for twohours. The samples were then dried using a vacuum concentrator at 45-55°C. and the samples were determined to be dry if, when the tube wasflicked the pellets did not move or spread.

Hybridization

125 μL of nuclease free water was added to the vial containinglyophilised 10×GE blocking agent supplied with the Agilent Kit andmixed. The dried sample was resuspended in 18 μL of nuclease free water.4.5 μL of the 10×GE blocking agent was added to each sample. 22.5 μL of2×Hi-RPM Hybridization buffer was added to each sample and mixed well.The resulting samples were incubated at 100° C. for 5 minutes, and thenimmediately transferred to an ice waterbath for a further 5 minutes. Aclean gasket slide was loaded into the Agilent SureHyb chamber baseensuring the gasket slide was flush with the chamber base. Thehybridization sample was dispensed onto the gasket well ensuring nobubbles were present.

An array was placed active side down onto the SureHyb gasket slide andassembled with the SureHyb chamber cover to form an assembled chamber.The assembled chamber was placed into 1 a hybridization oven set at 55°C. and rotated at 20 rpm for 20 hours at that temperature.

The arrays were subsequently washed using the supplied GE wash buffersbefore being scanned.

(2) Quantitative Real-Time PCR

Quantitative real-time PCR is carried out in three stages. The first twostages, to synthesise cDNA from the total RNA samples, use the qScriptmiRNA cDNA synthesis kit (Quanta Biosciences). The third step, QPCRreactions, use the SYBR Green PerfeCTa Low Rox Reaction Mix (QuantaBiosciences).

Poly(A) Tailing Reaction

Total RNA samples (of between 100 ng and 1 μg) are aliquoted into fresh0.5 ml tubes and made up to 7 μl with nuclease-free water. 2 μl of 5×PAP(Poly(A) Polymerase) Tailing Buffer and 1 μl of Poly(A) Polymerase isadded to each tube, then the tubes vortexed and centrifuged. The samplesare then incubated in a thermal cycler under the following conditions:37° C. for 20 minutes, then 70° C. for 5 minutes. Following thisreaction, samples are placed on ice.

cDNA Synthesis Reaction

A mastermix of RT is prepared so that each sample will receive 9 μl ofmiRNA cDNA Reaction Mix and 1 μl of qScript Reverse Transcriptase. 10 μlof this mix is added to each sample, then the tubes vortexed andcentrifuged. The samples are then incubated in a thermal cycler underthe following conditions: 42° C. for 20 minutes, then 85° C. for 5minutes. Following this reaction, samples are placed on ice and thendiluted 5-fold in 1×TE buffer. QPCR Reaction

A mastermix of SYBR Green reaction mix and primers is prepared so thateach sample well will receive the following kit components:

-   -   10 ul of 2×SYBR Green PerfeCTa Low Rox Reaction Mix    -   0.4 μl of UA3PA Universal Reverse primer (10□M)    -   0.4 μl of miRNA-specific primer (10□M)    -   4.2 μl of nuclease-free water

To each well, 5 μl of cDNA is added. When all the wells are filled, theplate is sealed with plastic optical lids and centrifuged to remove airbubbles. The plate is loaded into the Agilent MX3005P thermocycler andprocessed under the following cycling conditions:

-   -   95° C. for 2 minutes    -   (95° C. for 5 seconds, 60° C. for 30 seconds)×40 cycles    -   Fluorescence data is collected at the end of every        annealing/extension step

Data Analysis

Data from both of these techniques was normalised against the spike-inmiRNA spots for each plate, allowing data from separate arrays to becompared. Normalised data was analysed using Principal ComponentAnalysis, a standard technique well understood by those skilled in theart to identify correlations between miRNA expression profiles, and anygrouping of data observed determined to be a 15 consequence of theaction of the particular test condition in relation to the originalcells on the expression of the individual miRNA.

FIG. 1 is a flow diagram of a method for obtaining an expression profilefor micro RNA.

FIGS. 2A-2E the alterations in has-miR-210, hsa-miR1274a andhsa-miR-302c* between passage numbers identified by microarray analysisand confirmed by QPCR measurements of the mature microRNAs.

FIGS. 3A-3E show alterations in microRNA profiles in a serially-passagedhuman, tumour-derived cell lines (HeLa and MCF-7).

As can be seen in FIGS. 2A-2E, the results are clearly grouped and thatthis grouping is according to the passage number of the cells in whichthe miRNAs were expressed. In other words, it is possible to determinethat the replicate samples of identically-passaged cells have similarbut distinct miRNA expression profiles.

A database of miRNA expression patterns can be built up by carrying outmany comparisons of cell passage number and analysing the resultingchanges in miRNA expression. Such a database would enable identificationof phenotypic drift in pluripotent stem cells, or cell lines used inbioprocessing and indicate a loss of optimal functionality, in theformer case pluripotent potential, in the latter case productions of adesired macromolecule. Furthermore, building up a database of miRNAexpression data may reveal a subset of certain miRNAs that areindicative of an unfavourable or undefined alterations to cellphysiology. Once subsets of indicative miRNAs are identified, futuretesting of new cell lines can be carried out by looking at theexpression profiles of the subset of indicative miRNA expressionprofiles and not the entire range of miRNAs produced by the cells.miRNAs may be ranked in order of the relevance of their expressionlevels for discriminating between biological interventions, or betweengroups of interventions known or hypothesized to have similar effects oncell physiology. miRNAs may be allocated a numerical value indicative ofthe relevance of their expression levels for discriminating betweeninterventions, or between groups of interventions known or hypothesizedto have similar effects on the cells. For example, the numerical valuemay be related to the contribution of the expression level of a miRNA tothe variance of principle components. As an alternative to, or inaddition to, the comparison of miRNA expression profiles usingstatistical methods such as principal component analysis, the effectcell culture passages on the expression of each of a limited group ofmiRNAs (for example, 10-50) may be identified and used to assign a code,selected from a group of codes, to the effect of the biologicalintervention on the expression of each respective miRNA. The resultingcodes may be compared to identify similarities in effect.

For example, for comparison (e.g. cell passage number) a 3-digit binarynumber may be allocated as a code to each ranked miRNA based on:

-   -   1. If expression of the miRNA is unchanged (within normal limits        of experimental variability) in response to the biological        intervention, the first bit is set to 0. If expression has        changed significantly, the first bit is set to 1.    -   2. If a change in expression level was identified and the change        was an increase, the second bit is set to 1. If the change        resulting from the biological intervention was a decrease, the        second bit is set to 0.    -   3. If the change in expression level was more than 4-fold, the        third bit is set to 1, otherwise it is set to 0.

Thus, the effect of a difference between cell passages or cultureconditions on the expression of a miRNA is allocated a code having oneof five possible values:

-   -   4. No change 2 in expression—000    -   5. Large increase in expression—111    -   6. Small increase in expression—110    -   7. Large decrease in expression—111    -   8. Small decrease in expression—100

The effect extended time in culture (i.e., an increase in passagenumber) on the expression level of a group of miRNAs may becharacterised by the associated code, permitting identification ofchanges in expression level not immediately apparent from principalcomponent analysis, permitting alternative methods of scoring thesimilarity of test conditions or interventions and rendering theresulting expression data comprehensible by visual inspection.

Another way to characterise the effect of a cell maintenance regime andto determine correlations between the effects on miRNA expression ofdifferent biological interventions is to carry out an expression assayto determine the effects of an intervention on the expression of each ofa group (of typically 10 to 50) miRNAs and to rank the miRNAs in thatgroup in order of the effect, for example, in order from the miRNA inthe group which has the largest increase in expression to the miRNA inthe group which has the largest decrease in expression, or vice versa.The resulting rankings are indicative of the effects of particular testpoint or interventions. Thus, the effect of other interventions on thegroup of miRNAs may be measured and the miRNAs in the group ranked inorder of the effect. The resulting rankings may be compared to enablecorrelations between the effects of interventions to be identified.

A kit comprising plates operable to test the subset of indicative miRNAsmay be provided to significantly increase the efficiency and speed withwhich the effect of cell passage and/or interventions can be screenedfor potential novel therapeutic applications.

Further variations and modifications may be made within the scope of theinvention herein disclosed.

References

-   -   9. Xie, X., et al., Systematic discovery of regulatory motifs in        human promoters and 3′-UTRs by comparison of several mammals.        Nature, 2005. 434(7031): p. 338-45    -   2. Lim, L. P., et al., Microarray analysis shows that some        microRNAs downregulate large numbers of target mRNAs.        Nature, 2005. 433(7072): p. 769-73    -   3. Calin, G. A., et al., MicroRNA profiling reveals distinct        signatures in B cell chronic lymphocytic leukemias. Proc Natl        Acad Aci USA, 2004. 101 (32): p. 11755-60 EXAMPLE 2

Summary

-   -   10. MicroRNA profiling of serially-passaged stem cells reveals        differences in cells assessed to be ‘identical’ populations        using flow cytometry and a commercial kit assessing cell surface        and internal protein antigen markers of pluripotency and        differentiation, as shown in FIGS. 4A-4D.    -   11. micro-RNAs can be used to monitor the directed        differentiation of hESC to erythrocytes by comparing miRNA        profiles from two populations of CD34+ cells derived by directed        differentiation of human embryonic cell lines (hESCs) for        comparison with the equivalent developmental stage of adult        CD34+ haematopoietic stems cells (HSCs;), as shown in FIGS. 5A        and 5B.

Methods.

These are outlined in Example 1 above (see section headed “FlowCytometry” and “Data analysis”—in particular, PCA).

The hierarchical clustering and heatmap visualisation of the data wereachieved using Qlucore Omics Explorer (Qlucore AB).

A volcano plot is a graphical representation of that is used to quicklyidentify changes in large datasets composed of replicate data. It plotssignificance versus fold-change on the y- and x-axes, respectively. Thevolcano plot was generated using the results of an ANOVA analysis forthe hESC datasets. Both the ANOVA analysis and Volcanoes plot weregenerated using Partek's Genomic Suite (Partek, Inc).

Results and Discussion.

-   -   12. Identification of miRNA differences in pluripotent hESC cell        populations otherwise assessed to be identical.

Roslin Cellabs utilised a human embryonic stem cell line, RCM1. Cellswere obtained at mid-passage 51 (P51) and a late passage (P103), wherean individual passage (i.e. the period between cell sub-culturing) isabout 1-week. The cells were grown for up to three passagespost-resuscitation from liquid nitrogen storage in order to generatesufficient cells for analysis by flow cytometry and miRNA profiling.

Flow Cytometry, MicroRNA Profiling and Data Analysis

The cells from each passage were analysed using Flow Cytometry carriedout by Roslin Cells. This analysis, as shown in FIG. 4A, suggests thatboth cell populations are indistinguishable for the pluripotentcy anddifferentiation markers used in the commercial test. However, as can beseen in FIG. 4B below, the biological replicates (n=3) at each passageclearly group together according to the passage number of the cells inwhich the miRNAs were expressed. In other words, it is possible todetermine that the replicate samples of identically-passaged cells havesimilar but distinct miRNA expression profiles.

There were 5 differentially-expressed miRNAs with a fold-changedifference of 2 or more, as shown in FIG. 4C, and the identity of thesemiRNAs are given in FIG. 4D.

2. Monitoring hESC-Derived and Adult Haematopoietic Stem Cells Directedto Differentiate to Erythrocytes.

A PCA of the top 50 most variable miRNA transcripts is shown in FIG. 5Abelow. The samples cluster distinctly based on cell type and stage,which is also evident from the heatmap in FIG. 5B. For stage 1, the hESCand Adult HSC categories occupy separate spaces on the PCA plot,implying that these cell types have distinctly different properties. Atstage 2, however, the hESC and Adult HSC categories are largely groupingtogether, demonstrating that the miRNA profiles of the samples arehighly similar.

The following sample groups were analysed:

-   -   hESC stage 0: Undifferentiated hESC    -   hESC stage 1: hESC at day 10 of the differentiation protocol    -   hESC stage 2: hESC at day 24 of the differentiation protocol    -   Adult HSC stage 1: Adult HSC cells at a differentiation stage        equivalent to that of hESC stage 1    -   Adult HSC stage 2: Adult HSC cells at a differentiation stage        equivalent to that of hESC stage 2 (14 days after induction of        differentiation) Embodiments of this invention may relate to:

A method comprising steps of:

-   -   i. Growing cell lines as serially passaged cultures and at each        passage where the cells are sampled, determining the microRNA        expression profile, for example by microarraying, following a        defined intervention or where there is no change to the growth        conditions    -   ii. Define using a appropriate statistical test, for example        Principal Components Analysis, separation between samples based        on passage number, alterations to growth conditions, treatment        with drugs or other external factors, transfection/viral        transduction of gene(s)    -   iii. Determining the microRNAs which define the variation        between the test conditions These miRNAs can inform the ‘drift’        of the cells from optimally pluripotent, optimally        differentiating and/or optimally growing cells population and/or        those safe for their purpose in bioprocessing, drug discovery or        regenerative medicine i.e. reveal key information on the        identity, purity, potency or safety (tumourigenicity of stem        cells, microbiological contamination) of the cell population

Where the cells are mammalian (possibly human and/or rodent)undifferentiated, pluripotent, embryonic stem cells or iPS cells (whereiPS cells (induced pluripotent stem cells) are defined as adult somaticcells which have been reprogrammed by direct expression of exogenouscDNAs/mRNAs/miRs from one or more transduced vectors). In combinationsthat may include chemical entities necessary for their production.

Where the cells are a mixture of one or more of the primary germ layersor progenitor cells derived from hESC or iPS cells

Where the cells are mirPS cells (from Mello Inc) or other cellsreprogrammed by direct expression of exogenous miRNA(s) form one or moretransduced vectors.

Where the biological system represents plasmid-based assay systems,controllably inserted into the hESC genome and have them activelyexpress in pluripotent as well as in differentiated lineages derivedfrom the genetically engineered cells.

Where tissue-specific stem cells are used to produce one or moreterminally differentiated lineages following exposure to biologicalfactors and/or chemical entities that direct differentiation

Where the cells are human or animal multipotent mesenchymal stem cellsor any other adult stem cell population

Where the cells are primary cell cultures derived from human or animaltissues

Where the cells are established cell lines with and without geneticmodifications (e.g. with virus or plasmid-based expression of anexogenous enzyme, protein or peptide)

Where the change in growth conditions includes alterations in cellmatrix, including switching from 2-dimensional to 3-dimensional culturesystems, cell media composition, addition of xenogenic components,drugs, excipients and chemicals, including those used for cosmetics,exposure to biological agents & their biosimilars, variations physicalconditions (e.g temperature, radiation etc.).

Monitor commitment towards specific lineages following exposure to smallmolecules and biological factors (biologies or biosimilars), eitheralone or in combination.

For bioprocessing application specifically, monitor the effects inalterations dues to pH, osmolality etc.

Others relating to the way the microRNAs are changing—positive ornegative correlations as well as combinations of microRNA changes i.e.the pattern of miR changes defines the alteration to cell phenotype.

1.-15. (canceled)
 16. A method of quality assessing stem cells cultured from an in vitro cell culture system for use in stem cell therapy, said method comprising the steps of: providing a stem cell sample from the stem cell culture, providing an assay and/or reagents for obtaining microRNA profiles from the stem cell samples and comprising a predetermined panel of microRNAs, providing a reference expression profile of the predetermined panel of microRNAs which is derived from a stem cell sample that conforms to a predetermined standard for the use of stem cells in stem cell therapy, the predetermined panel of microRNAs selected as being proxy to certain quality characteristics consistent with the predetermined standard for the use of stem cells in stem cell therapy, employing a microRNA expression assay with the stem cell sample for the predetermined panel of microRNAs to obtain a microRNA expression profile for the stem cell sample, comparing the microRNA profile of said stem cell sample with the reference microRNA expression profile, determining from the comparison a quality assessment of the stem cell sample for use in stem cell therapy and, dependent upon the quality assessment, determining the suitability of the stem cell sample for use in stem cell therapy, and supplying stem cells from the stem cell culture for use in stem cell therapy.
 17. The method according to claim 16 wherein the panel includes microRNAs that are markers of undesirable or uncharacterized alterations in the cell system.
 18. The method according to claim 16, wherein the qualities being assessed are the maintenance of cell identity and functional capability.
 19. The method according to claim 16, wherein the predetermined panel of microRNAs includes microRNAs derived from cells of known identity and/or known functional capability and determined to be a marker of the cells identity and/or functional capability.
 20. The method according to claim 16, wherein the qualities being assessed are selected from one or more of phenotype, low contamination level and viability in accordance with a predetermined standard.
 21. The method according to claim 20, wherein the predetermined panel of microRNAs includes microRNAs derived from one or more cells of known phenotypes, contamination levels selected from no or low contamination levels and moderate or high contamination levels, and viability, and determined to be a marker of a desired and an undesired quality of one or more of phenotype, contamination level and viability.
 22. The method according to claim 16, wherein the quality being assessed is potency of stem cells.
 23. The method according to claim 22, wherein the predetermined panel of microRNAs includes microRNAs derived from stem cells of known potency and determined to be a marker between a desired and an undesired stem cell potency.
 24. The method according to claim 16, wherein the reference expression profile of the panel of microRNAs which is derived from a stem cell sample that conforms to a predetermined standard for the use of stem cells in stem cell therapy is a reference expression profile of a stem cell population cultured according to a particular protocol which stem cell population conforms to a predetermined standard for use in stem cell therapy.
 25. The method according to claim 24, wherein the predetermined panel of microRNAs include at least one microRNA as a marker for altered culture conditions over the particular culture protocol.
 26. The method according to claim 25, wherein the step of providing the reference microRNA expression profile comprises providing a reference stem cell sample that conforms to a predetermined standard for the use of stem cells in stem cell therapy and employing a microRNA expression assay with the reference cell sample for the panel of microRNAs contemporaneously with the stem cell sample being quality assessed.
 27. The method according to claim 16, wherein the step of providing the reference microRNA expression profile comprises providing a database of the microRNA expression profiles derived from a stem cell sample that conforms to a predetermined standard for the use of stem cells in stem cell therapy.
 28. The method according to claim 16, wherein the step of comparing the microRNA expression profile of the cell sample with the reference expression profile comprises identifying correlations between microRNA profiles.
 29. The method according to claim 28, wherein the correlations may comprise positive and/or negative correlations between the expression of one or more microRNAs.
 30. The method according to claim 29, wherein a positive correlation is an expression of a microRNA in the sample to be quality assessed and in the reference microRNA profile and a negative correlation is expression of a microRNA in the sample to be quality assessed which exhibits differential expression in the reference microRNA profile.
 31. The method according to claim 16, wherein the stem cells are induced pluripotent stem cells.
 32. The method according to claim 16, wherein the stem cells are mesenchymal stem cells.
 33. A method of quality assessing stem cells cultured from an in vitro cell culture system for use in stem cell therapy, said method comprising: employing a microRNA expression assay with a stem cell sample from a stem cell culture for a predetermined panel of microRNAs, selected as being proxy to certain quality characteristics consistent with the predetermined standard for the use of stem cells in stem cell therapy, to obtain a microRNA expression profile for the stem cell sample, wherein a comparison of the microRNA profile of said stem cell sample with a reference microRNA expression profile of the predetermined panel of microRNAs which reference microRNA expression profile is derived from a stem cell sample that conforms to a predetermined standard for the use of stem cells in stem cell therapy, allows for a determination of a quality assessment of the stem cell sample for use in stem cell therapy, and depending upon the quality assessment, allows for a determination of the suitability of the stem cell sample for use in stem cell therapy, and optionally supplying stem cells from the stem cell culture for use in stem cell therapy.
 34. A kit comprising a database of non-coding RNA profiles obtained from cells having known characteristic(s) and/or a known profile and an assay and/or reagents for obtaining non-coding RNA profiles from cells to be characterized, profiled and/or quality controlled. 